Own and evolve the safety layer that runs independently of perception, planning, and learned policies, and extend it to new wheeled, legged, and humanoid platforms
Build runtime monitors and collision avoidance backstops that check every commanded motion against the environment before it reaches the robot
Enforce speed, zone, terrain, and proximity limits, and define the safe operating envelope for each platform and deployment
Design fallback and minimal risk behaviors, from graceful slow down to safe stop, and the logic that decides when to trigger them
Build watchdogs and health monitoring across sensors, compute, communication, and actuation, so the robot always knows when it can trust itself
Lead hazard analysis and safety case development for new platforms and new deployments
Verify the safety layer in simulation, hardware-in-the-loop (HIL) testing, and field trials, with coverage that grows with every deployment
Work with planning, control, locomotion, and integration teams so the nominal stack plans and moves within the safety envelope
Master’s degree or higher in Robotics, Computer Science, Electrical Engineering, or a related field, or a Bachelor’s degree with substantial hands-on experience on safety related autonomous systems
2+ years of experience developing safety, monitoring, or fallback systems for robots or autonomous vehicles
Strong grounding in classical planning and control, such as collision checking and trajectory validation
Experience writing deterministic, real time, resource bounded C++ for systems where correctness matters more than features
Solid Python skills for tooling, analysis, and test automation in Linux-based environments
A verification mindset: you think in terms of assumptions, failure modes, coverage, and evidence
Familiarity with safety standards for mobile robots and autonomous systems (e.g., ISO 13482, ISO 3691-4, ISO 26262)
Familiarity with robotics middleware such as ROS/ROS 2, and with robot sensors such as LiDAR, depth cameras, and IMUs
Functional safety experience in autonomous vehicles, industrial robots, or aerospace
Experience with runtime assurance architectures that wrap a learned or complex controller
Experience with formal or set based safety methods applied to real robots
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